Adaptive energy-efficient location determination

ABSTRACT

Managing use of a location sensor on a computing device for energy efficiency. The location sensor is briefly initialized to measure the signal quality. The measured signal quality is compared to pre-defined signal criteria values. The signal criteria values correspond to acceptable energy consumption, for example. If the signal criteria values are satisfied, location information for the computing device is obtained. Otherwise, the location sensor is disabled without obtaining the location information. In some embodiments, a lower-energy location sensor is used to obtain location information to determine whether to enable a higher-energy location sensor based on expected energy consumption.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of commonly-owned, U.S. patentapplication Ser. No. 12/766,208, filed Apr. 23, 2010, the entiredisclosure of which is hereby incorporated by reference herein for allpurposes.

BACKGROUND

Many mobile devices such as cellular telephones are equipped withlocation sensors such as global positioning system (GPS) receiversand/or other location sensing technology. While providing a valuablefunction, continual use of the location sensors by various positioningservices executing on the mobile devices keeps the location sensorsenergized. The cost of continually energizing the location sensors isoften expensive in terms of energy consumption. The already-limitedbattery life of the mobile devices is further shortened. Existingsystems fail to manage usage of the location sensors to optimize energyconsumption of the location operations.

SUMMARY

Embodiments of the disclosure enable energy-efficient locationdetermination on a computing device. A location sensor associated withthe computing device is enabled. One or more signal quality values ofthe location sensor are measured. The measured signal quality values arecompared to one or more corresponding predefined signal criteria values.If the measured signal quality values satisfy the predefined signalcriteria values, location information is obtained via the locationsensor. Otherwise, the location sensor is disabled without obtaining thelocation information.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an exemplary block diagram illustrating a mobile computingdevice detecting one or more nearby beacons.

FIG. 2 is an exemplary block diagram illustrating a computing devicehaving a location sensor and storing criteria values.

FIG. 3 is an exemplary flow chart illustrating operation of a computingdevice to selectively proceed with determining location informationbased on signal quality.

FIG. 4 is an exemplary block diagram illustrating a mobile computingdevice.

FIG. 5 is an exemplary flow chart illustrating operation of a computingdevice to selectively proceed with determining location informationbased on a cost of a previous location determination.

Corresponding reference characters indicate corresponding partsthroughout the drawings.

DETAILED DESCRIPTION

Referring to the figures, embodiments of the disclosure enable computingdevices to manage use of location sensors 204 for energy efficiency. Insome embodiments, signal quality information is briefly collected afterinitiating a location sensing operation. The collected information iscompared to thresholds to determine whether to proceed with the locationsensing operations. Some embodiments contemplate building an energyconsumption profile mapping energy consumption by a computing device toparticular locations. The energy consumption profile is subsequentlyused by the computing device to determine whether a location sensingsession at a particular location may be energy-inefficient. The energyconsumption profiles of the computing devices may be stored and/orshared via a community-based cloud service 418.

Referring again to FIG. 1, an exemplary block diagram illustrates amobile computing device 102 detecting one or more nearby beacons. Themobile computing device 102 (e.g., a mobile telephone) detects orobserves one or more beacons including cellular towers (or sectors ifdirectional antennas are employed), wireless fidelity (Wi-Fi) accesspoints, satellites, or other wireless access points (WAPs) via one ormore location sensors 204 of the mobile computing device 102.

The beacons detected by the mobile computing device 102 at a given pointin time represent a beacon fingerprint. The beacon fingerprint may alsoinclude other attributes of the detection or connection with the beaconssuch as signal quality, as discussed in detail below. While aspects ofthe disclosure may be described with reference to beacons implementingprotocols such as the 802.11 family of protocols, embodiments of thedisclosure are operable with any beacon for wireless communication. Inthe example of FIG. 1, the mobile device 102 detects the presence ofbeacons C1, C3, W1, W3, S1, S2, and S3.

A time-to-first-fix (TTFF) value represents the amount of time elapsedbetween enabling the location sensors 204 until location information isavailable. The TTFF value may vary based on a location of the mobilecomputing device 102.

Referring next to FIG. 2, an exemplary block diagram illustrates acomputing device 202 having a location sensor 204 and storing criteriavalues. The computing device 202 includes, for example, a mobilecomputing device such as mobile computing device 102 enabled with aglobal positioning system (GPS) receiver such as part of assisted GPS, aradio such as in a wireless fidelity (Wi-Fi) positioning system or acellular-based positioning system or a BLUETOOTH brand communicationsystem, a three-dimensional motion sensor, or other element as thelocation sensor 204.

However, the device may include any device executing instructions (e.g.,application programs) to provide data including detected beacons. Insome embodiments, the device includes a portable computing device suchas a laptop, netbook, gaming device, and/or portable media player.Further, the device may represent a group of processing units or othercomputing devices.

The memory area 206 includes any quantity of media associated with oraccessible to the computing device 202. The memory area 206 may beinternal to the computing device 202 (as shown in FIG. 2), external tothe computing device 202 (not shown), or both (not shown). The memoryarea 206 stores one or more signal criteria values 208 and an elapsedtime criteria value 210. These values 208, 210 are used by the computingdevice 202 as thresholds against which characteristics of connectionswith nearby detected beacons are compared.

Referring next to FIG. 3, an exemplary flow chart illustrates operationof the computing device 202 to selectively proceed with determininglocation information based on signal quality. Via the operationsillustrated in FIG. 3, the computing device 202 is able to brieflyinitiate a location sensing session to collect signal qualityinformation to determine whether to proceed or abort the session. Forexample, GPS satellite signals are often obstructed indoors. The cost ofobtaining a GPS position indoors, if even possible, may be high in thatthe TTFF may take several minutes and have a high energy-per-fix cost.In such situations, aspects of the disclosure may not proceed to obtainthe location information.

At 302, the location sensor 204 associated with the computing device 202is enabled. For example, the location sensor 204 may be energized,powered, probed, or otherwise modified to make available thecapabilities of the location sensor 204 for location determination.Exemplary location sensors 204 include, but are not limited to, a GPSreceiver or a Wi-Fi adapter.

At 304, one or more signal quality values of the enabled location sensor204 are measured. Exemplary signal quality values include, but are notlimited to, a signal strength or a signal-to-noise ratio. In embodimentsin which the location sensor 204 is a GPS receiver, exemplary signalquality values include a quantity of satellites observed by the GPSreceiver. In other embodiments, measuring the signal quality valuesincludes exchanging data with a wireless access point.

At 306, one or more of the signal criteria values 208 are accessed. Thesignal criteria values 208 represent thresholds, standards, costs,minimum acceptable criteria, or maximum acceptable criteria by which tojudge the measured signal quality values. The signal criteria values 208may be determined empirically or dynamically (e.g., based on an averageor mean calculation), defined by a user of the computing device 202, orcalculated or derived from other values (e.g., cost values). In someembodiments, prior to measuring the signal quality values at 304, thesignal criteria values 208 are dynamically defined. For example, thesignal criteria values 208 may be defined or adjusted based onpreviously measured signal quality values. This allows the operations inFIG. 3 to accommodate changing environments, contexts, or computingdevice 202 status or configuration. Some embodiments include differentsignal criteria values 208 based on location, time (e.g., time-of-day),computing device 202, or condition of the computing device 202. Forexample, the high-energy consumption associated with a poor signalquality may be unacceptable during daylight, but acceptable at nighttimewhen there may be a greater desire to obtain the location information.

For example, in embodiments in which the location sensor 204 is a GPSreceiver, the signal criteria values 208 may include a minimum quantityof satellites observed by the GPS receiver. In other embodiments, thesignal criteria values 208 specify a maximum acceptable signal-to-noiseratio (e.g., 20 dB) or a minimum signal strength. In still otherembodiments, the signal criteria values 208 correspond to a financialcost (e.g., connection fees, etc.) or an energy cost (e.g., batteryconsumption) for obtaining the location information.

At 308, the measured signal quality values are compared to one or moreof the accessed signal criteria values 208. If the measured signalquality values satisfy the signal criteria values 208 at 308, thelocation information for the computing device 202 is obtained at 310 viathe location sensor 204. If the measured signal quality values fail tosatisfy the accessed signal criteria values 208 at 308, the locationsensor 204 is disabled at 312 without obtaining the locationinformation.

Satisfying the signal criteria values 208 may include, for example,determining that each of the measured signal quality values satisfiesthe corresponding signal criteria values 208, determining that at leastone of the measured signal quality values satisfies the correspondingsignal criteria value 208, or determining that a particular combination(e.g., a weighted combination) of the measured signal quality valuessatisfies the corresponding signal criteria values 208. For example, themeasured signal strength may be weighted more heavily than the measuredsignal-to-noise ratio such that the location information is obtained ifthe measured signal strength satisfies the corresponding signal criteriavalue 208 even though the measured signal-to-noise ratio fails tosatisfy the corresponding signal criteria value 208.

Satisfying the signal criteria values 208 may include, for example,determining that the measured signal quality values are less than, aregreater than, are equal to, or otherwise do not violate the signalcriteria values 208. Conversely, failing to satisfy the signal criteriavalues 208 may include, for example, determining that the measuredsignal quality values are less than, are greater than, are equal to, orotherwise violate the signal criteria values 208.

In some embodiments, the amount of time spent measuring the signalquality values also affects whether the location information is obtainedat 310. For example, an elapsed time value is measured or calculatedwhile measuring the signal quality values. If the measurement of theelapsed time value exceeds the elapsed time criteria value 210 (e.g., 60seconds), the location sensor 204 is disabled without obtaining thelocation information. The elapsed time criteria value 210 may also bereferred to as a timeout value for measuring the signal quality values.

In some embodiments, the operations illustrated in FIG. 3 are performedby the computing device 202. In other embodiments, one or more of theoperations illustrated in FIG. 3 are performed by another computingdevice (e.g., as a web service).

Referring next to FIG. 4, an exemplary block diagram illustrates themobile computing device 102 communicating with the community-based cloudservice 418. The elements illustrated in FIG. 4 operate to provideenergy-efficient location determination on the mobile computing device102.

The mobile computing device 102 has at least one processor 402, aplurality of location sensors 204, and one or more computer-readablemedia such as a memory area 404. The processor 402 includes any quantityof processing units, and is programmed to execute computer-executableinstructions for implementing aspects of the disclosure. Theinstructions may be performed by the processor 402 or by multipleprocessors executing within the mobile computing device 102, orperformed by a processor external to the mobile computing device 102. Insome embodiments, the processor 402 is programmed to executeinstructions such as those illustrated in the figures (e.g., FIG. 4 andFIG. 5).

The location sensors 204, such as location sensor #1 through locationsensor #N, include any element for communicating with another device toobtain location information or data from which to derive the locationinformation. For example, the location sensor 204 may include a GPSreceiver, a Wi-Fi adapter, a BLUETOOTH brand communication serviceelement, or the like.

The memory area 404 includes any quantity of media associated with oraccessible to the mobile computing device 102. The memory area 404 maybe internal to the mobile computing device 102 (as shown in FIG. 4),external to the mobile computing device 102 (not shown), or both (notshown).

The memory area 404 stores a plurality of location information costvalues 406 such as location information cost value #1 through locationinformation cost value #M. The location information cost values 406 areassociated with a mobility pattern of the mobile computing device 102.The location information cost values 406 represent the costs ofobtaining location information for the mobile computing device 102 whilethe mobile computing device 102 is in particular locations. The mobilitypattern represents a pattern of movement of the mobile computing device102 over a period of time (e.g., hours, days, weeks). The mobilitypattern has a plurality of locations associated therewith. For example,the mobility pattern may indicate that the mobile computing device 102moves between two locations (e.g., work and home) each day. The locationinformation cost values 406 are computed and stored in the memory area404 as the mobile computing device 102 moves around determining locationinformation.

The memory area 404 further stores at least one cost criteria value 408.The cost criteria value 408 represents a threshold cost (e.g., maximumacceptable cost) of obtaining the location information for the mobilecomputing device 102. In some embodiments, the cost criteria value 408includes a plurality of values each associated with a particularlocation. This enables the importance of obtaining the locationinformation to be differentiated among particular locations. Forexample, obtaining the location information near a downtown area withhigh-rise buildings may have a high cost, but the user or mobilecomputing device 102 has deemed the value of obtaining the locationinformation at this location to be high. The cost criteria value 408 forthis location is then set accordingly (e.g., higher than other costcriteria values 408). In another example, obtaining the locationinformation near the home of the user may have an average cost, but mayprovide less value to the user because the user is familiar with theneighborhood. The cost criteria value 408 for this location is then setlower than other cost criteria values 408.

The cost criteria value 408 may also include a plurality of values eachassociated with a particular time or range of times during the day. Forexample, a high cost for obtaining the location information may beacceptable at night when there is a stronger desire to obtain thelocation information. The cost criteria value 408 in this example isthen set to a higher value relative to the other cost criteria values408 to enable the mobile computing device 102 to obtain the locationinformation. The cost criteria value 408 may also vary based on time ofday, computing device, condition of the computing device, and/or otherfactors.

The memory area 404 further stores one or more computer-executablecomponents for implementing aspects of the disclosure. The componentsexecute to profile an environment of the mobile computing device 102opportunistically during usage of the location sensors 204 to record anenergy consumption profile. For example, every time the location sensor204 is turned on in a particular location by the user, an applicationprogram, or other triggering event, the energy consumption profile(e.g., a TTFF value) is calculated and associated with the location(e.g., a beacon fingerprint). The energy consumption profile isrepresented in some embodiments as the location information cost values406 (e.g., energy-per-fix values). The components further execute toavoid expensive location determination sessions based on the locationinformation cost values 406 and instead opt to perform energy-efficientlocation determination sessions. In one example of FIG. 4, radiofrequency fingerprints are acquired with low energy to identify theenvironments where efficient GPS fixes are probable.

In particular, exemplary components include a first sensor component410, a memory component 412, a threshold component 414, and a secondsensor component 416. The first sensor component 410, when executed bythe processor 402, causes the processor 402 to enable (e.g., energize)one of the location sensors 204 (e.g., a first location sensor) andobtain location information (e.g., first location information) from thefirst location sensor during a session. For example, the first locationsensor is a Wi-Fi adapter and the first location information is a beaconfingerprint (e.g., set of observed beacons). The memory component 412,when executed by the processor 402, causes the processor 402 to accessthe memory area 404 on the mobile computing device 102 to retrieve thelocation information cost value 406 associated with the first locationinformation (e.g., a beacon fingerprint). The threshold component 414,when executed by the processor 402, causes the processor 402 to comparethe retrieved location information cost value 406 to the cost criteriavalue 408 stored in the memory area 404.

If the retrieved location information cost value 406 satisfies the costcriteria value 408, the second sensor component 416, when executed bythe processor 402, causes the processor 402 to enable another locationsensor (e.g., a second location sensor) and to obtain additionallocation information (e.g., second location information) via the secondlocation sensor. For example, the second location sensor is a GPSreceiver and the second location information includes GPS coordinates.If the retrieved location information cost value 406 fails to satisfythe cost criteria value 408, the session closes without enabling thesecond location sensor.

The second sensor component 416 may further operate to calculate anupdated location information cost value based on a calculated cost ofthe second location information. For example, the location informationcost value 406 may be updated after a pre-configured quantity oflocation sensing operations (e.g., calculate an average locationinformation cost value after ten sessions) or after each session.

The updated location information cost value is provided to thecommunity-based cloud service 418 for storage and/or cached locally onthe mobile computing device 102. The mobile computing device 102 is thusable to adapt its operation based on current location information costvalues 406.

Some embodiments contemplate the first location sensor consuming lessenergy than the second location sensor. In such embodiments, the mobilecomputing device 102 is able to use the lower-energy location sensor todetermine whether to even enable the higher-energy location sensor, thusreducing energy consumption on the mobile computing device 102.

Storing each of the location information cost values 406 in the limitedcache on the mobile computing device 102 may consume the cache. As such,the plurality of location information cost values 406 calculated by orotherwise associated with the mobile computing device 102 are storedremotely from the mobile computing device 102. As the mobility patternemerges, the mobile computing device 102 obtains the locationinformation cost values 406 associated with the locations included inthe mobility pattern. The mobile computing device 102 thus caches on themobile computing device 102 the location information cost values 406that are expected to be accessed frequently based on the mobilitypattern. In the example of FIG. 4, the location information cost values406 for the mobile computing device 102 are stored in thecommunity-based cloud service 418.

In still further embodiments as described below with reference to FIG.5, the location information cost values 406 obtained by the mobilecomputing device 102 may not be associated with or previously calculatedby the mobile computing device 102. Rather, the location informationcost values 406 stored by the community-based cloud service 418 areaggregated from a plurality of computing devices and then shared withthe plurality of computing devices upon request. For example, the mobilecomputing device 102 may obtain the location information cost values 406associated with an expected mobility pattern (e.g., a navigation routeassociated with an upcoming trip).

At least a portion of the functionality of the various elements in FIG.4 may be performed by other elements in FIG. 4, or an entity (e.g.,processor, web service, server, application program, computing device,etc.) not shown in FIG. 4.

Referring next to FIG. 5, an exemplary flow chart illustrates operationof the mobile computing device 102 to selectively proceed withdetermining location information based on a cost of a previous locationdetermination. In the example of FIG. 5, the location information costvalues 406 are aggregated from a plurality of computing devices as ashared community resource. Mobile computing devices that enterparticular locations thus benefit from the experiences of mobilecomputing devices that have entered the particular locations previously.

At 502, the mobility pattern of the mobile computing device 102 isdefined. The community-based cloud service 418 is accessed at 504 toobtain the location information cost values 406 associated with thedefined mobility pattern. For example, the location information costvalues 406 stored by the community-based cloud service 418 arepartitioned into tiles based on geographical location. The obtainedlocation information cost values 406 represent a set of the locationinformation cost values 406 personalized to the mobile computing device102 based on the defined mobility pattern. At 506, the obtained locationinformation cost values 406 are cached locally by the mobile computingdevice 102. First location information is obtained from the firstlocation sensor at 508. The first location information is used at 510 toretrieve, from the local cache on the mobile computing device 102, thelocation information cost value 406 associated with a location describedby the first location information. In some embodiments, there areseparate location information cost values 406 for each second locationsensor available to the mobile computing device 102. The retrievedlocation information cost value 406 is compared at 512 to the costcriteria value 408. If the location information cost value 406 satisfiesthe cost criteria value 408, the second location information is obtainedfrom the second location sensor at 514. Otherwise, the session is closedat 516 without enabling the second location sensor and obtaining thesecond location information.

Alternatively or in addition to the location information cost value 406,other data may also be stored and retrieved. For example, the data mayidentify and prioritize or rank ways to configure and use the locationsensor(s) at different locations. For example, when Wi-Fi scanning athome or near a neighborhood of the mobile computing device 102, aparticular subset of the possible Wi-Fi channels may be identified forscanning.

In some embodiments, the operations illustrated in FIG. 5 are performedby the mobile computing device 102. In other embodiments, one or more ofthe operations illustrated in FIG. 5 are performed by another computingdevice (e.g., as a web service). Further, the operations illustrated inFIG. 5 may be implemented as software instructions encoded on acomputer-readable medium, in hardware programmed or designed to performthe operations, or both.

Additional Examples

In some embodiments, the location information cost values 406 arerepresented as energy-per-fix values quantifying the amount of energyconsumed to obtain location information. Exemplary energy-per-fix valuesrange from 1500 mJ to obtain a low-level coarse location fix to 2500 mJfor a high-level precise fix.

While embodiments have been described with reference to data collectedfrom users, aspects of the disclosure provide notice to the users of thecollection of the data (e.g., via a dialog box or preference setting)and the opportunity to give or deny consent. The consent may take theform of opt-in consent or opt-out consent.

Exemplary Operating Environment

Exemplary computer readable media include flash memory drives, digitalversatile discs (DVDs), compact discs (CDs), floppy disks, and tapecassettes. By way of example and not limitation, computer readable mediacomprise computer storage media and communication media. Computerstorage media store information such as computer readable instructions,data structures, program modules or other data. Communication mediatypically embody computer readable instructions, data structures,program modules, or other data in a modulated data signal such as acarrier wave or other transport mechanism and include any informationdelivery media. Combinations of any of the above are also includedwithin the scope of computer readable media.

Although described in connection with an exemplary computing systemenvironment, embodiments of the invention are operational with numerousother general purpose or special purpose computing system environmentsor configurations. Examples of well known computing systems,environments, and/or configurations that may be suitable for use withaspects of the invention include, but are not limited to, mobilecomputing devices, personal computers, server computers, hand-held orlaptop devices, multiprocessor systems, gaming consoles,microprocessor-based systems, set top boxes, programmable consumerelectronics, mobile telephones, network PCs, minicomputers, mainframecomputers, distributed computing environments that include any of theabove systems or devices, and the like.

Embodiments of the invention may be described in the general context ofcomputer-executable instructions, such as program modules, executed byone or more computers or other devices. The computer-executableinstructions may be organized into one or more computer-executablecomponents or modules. Generally, program modules include, but are notlimited to, routines, programs, objects, components, and data structuresthat perform particular tasks or implement particular abstract datatypes. Aspects of the invention may be implemented with any number andorganization of such components or modules. For example, aspects of theinvention are not limited to the specific computer-executableinstructions or the specific components or modules illustrated in thefigures and described herein. Other embodiments of the invention mayinclude different computer-executable instructions or components havingmore or less functionality than illustrated and described herein.

Aspects of the invention transform a general-purpose computer into aspecial-purpose computing device when configured to execute theinstructions described herein.

The embodiments illustrated and described herein as well as embodimentsnot specifically described herein but within the scope of aspects of theinvention constitute exemplary means for energy-efficient locationdetermination on the mobile computing device 102 using two locationsensors 204, and exemplary means for energy-efficient locationdetermination on the mobile computing device 102 by usingcommunity-based location information cost values 406.

The order of execution or performance of the operations in embodimentsof the invention illustrated and described herein is not essential,unless otherwise specified. That is, the operations may be performed inany order, unless otherwise specified, and embodiments of the inventionmay include additional or fewer operations than those disclosed herein.For example, it is contemplated that executing or performing aparticular operation before, contemporaneously with, or after anotheroperation is within the scope of aspects of the invention.

When introducing elements of aspects of the invention or the embodimentsthereof, the articles “a,” “an,” “the,” and “said” are intended to meanthat there are one or more of the elements. The terms “comprising,”“including,” and “having” are intended to be inclusive and mean thatthere may be additional elements other than the listed elements.

Having described aspects of the invention in detail, it will be apparentthat modifications and variations are possible without departing fromthe scope of aspects of the invention as defined in the appended claims.As various changes could be made in the above constructions, products,and methods without departing from the scope of aspects of theinvention, it is intended that all matter contained in the abovedescription and shown in the accompanying drawings shall be interpretedas illustrative and not in a limiting sense.

What is claimed is:
 1. A system for energy-efficient locationdetermination on a mobile computing device, said system comprising: amemory area associated with the mobile computing device; and a processorprogrammed to: define a mobility pattern of the mobile computing device;obtain location information cost values based on the defined mobilitypattern from a community-based cloud service; store the obtainedlocation information cost values in the memory area associated with themobile computing device; energize a location sensor associated with themobile computing device; measure one or more signal quality values ofthe energized location sensor; compare the measured signal qualityvalues with a predefined signal criteria value; on determining that themeasured signal quality values satisfy the predefined signal criteriavalue, obtain a location information via the energized location sensor;and on determining that the measured signal quality values do notsatisfy the predefined signal criteria value, de-energize the locationsensor without obtaining the location information.
 2. The system ofclaim 1, wherein if the obtained location information cost valuessatisfy the predefined cost criteria value, the processor is programmedto obtain additional location information by: energizing one otherlocation sensor; measuring one or more signal quality values of theenergized other location sensor; comparing the measured signal qualityvalues of the energized other location sensor with a plurality of signalcriteria values; obtaining the additional location information via theenergized other location sensor if the measured signal quality values ofthe enabled other location sensor satisfy the plurality of signalcriteria values; and otherwise de-energizing the other location sensorwithout obtaining the additional location information.
 3. The system ofclaim 2, wherein the processor is further programmed to determine anelapsed time value associated with measurement of the signal qualityvalues.
 4. The system of claim 3, wherein the processor is programmed toobtain the additional location information if the determined elapsedtime value is less than a predefined elapsed time criteria value.
 5. Thesystem of claim 2, wherein the location sensor comprises a radio and theother location sensor comprises a global positioning system receiver. 6.The system of claim 1, wherein the location sensor comprises at leastone of a Wi-Fi adapter, a global positioning system receiver, acellular-based positioning system receiver, or a three-dimensionalmotion sensor.
 7. The system of claim 1, wherein measuring the one ormore signal quality values comprises exchanging data with a wirelessaccess point.
 8. A method comprising: defining a mobility pattern of acomputing device; obtaining location information cost values based onthe defined mobility pattern from a community-based cloud service;storing the obtained location information cost values in a memory area;energizing a location sensor associated with the computing device;measuring one or more signal quality values of the energized locationsensor; comparing the measured signal quality values with one or morepredefined signal criteria values; obtaining location information viathe energized location sensor if the measured signal quality valuessatisfy the predefined signal criteria values; and otherwisede-energizing the location sensor without obtaining the locationinformation.
 9. The method of claim 8, wherein the location sensorcomprises a global positioning system receiver, and wherein measuringthe signal quality values comprises determining at least one of a signalstrength value, a signal-to-noise ratio, or a quantity of observedsatellites.
 10. The method of claim 8, wherein measuring the one or moresignal quality values comprises exchanging data with a wireless accesspoint.
 11. The method of claim 8, further comprising, prior to measuringthe one or more signal quality values, dynamically defining thepredefined signal criteria values based on previously-measured signalquality values.
 12. The method of claim 8, further comprisingdetermining an elapsed time value associated with measuring the signalquality values.
 13. The method of claim 12, wherein obtaining thelocation information comprises obtaining the location information if thedetermined elapsed time value is less than a predefined elapsed timecriteria value.
 14. The method of claim 8, wherein comparing themeasured signal quality values with the one or more correspondingpredefined signal criteria values further comprises comparing themeasured signal quality values of one or more connections between thecomputing device and nearby beacons with the one or more correspondingpredefined signal criteria values.
 15. One or more computer storagedevices storing computer-executable instructions that, upon execution,cause at least one processor to: define a mobility pattern of a mobilecomputing device; obtain location information cost values based on thedefined mobility pattern; store the obtained location information costvalues in the memory area associated with the mobile computing device;energize a location sensor associated with the mobile computing device;measure one or more signal quality values of the energized locationsensor; compare the measured signal quality values with one or morecorresponding predefined signal criteria values; obtain locationinformation from the location sensor if the measured signal qualityvalues satisfy the predefined signal criteria values; and otherwisede-energize the location sensor without obtaining the locationinformation.
 16. The computer storage devices of claim 15, wherein thecomputer-executable instructions further cause the processor to retrievethe location information cost values from the memory area.
 17. Thecomputer storage devices of claim 16, wherein if the retrieved locationinformation cost values satisfy a predefined cost criteria value, thecomputer-executable instructions further cause the processor to:energize one other location sensor associated with the computing device;measure one or more signal quality values of the energized otherlocation sensor; compare the measured signal quality values of theenergized other location sensor with the predefined signal criteriavalues; obtain additional location information via the energized otherlocation sensor if the measured signal quality values of the energizedother location sensor satisfy the predefined signal criteria values; andotherwise de-energize the other location sensor without obtaining theadditional location information.
 18. The computer storage devices ofclaim 17, wherein energizing the location sensor causes consumption ofless energy than energizing the other location sensor.
 19. The computerstorage devices of claim 16, wherein the location information cost valuecomprises at least one of an energy-per-fix value or a financial costvalue.
 20. The computer storage devices of claim 15, wherein thelocation sensor comprises at least one of a radio, a global positioningsystem receiver, a cellular-based positioning system receiver, or athree-dimensional motion sensor.